CN107504971A - A kind of indoor orientation method and system based on PDR and earth magnetism - Google Patents
A kind of indoor orientation method and system based on PDR and earth magnetism Download PDFInfo
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- CN107504971A CN107504971A CN201710544039.3A CN201710544039A CN107504971A CN 107504971 A CN107504971 A CN 107504971A CN 201710544039 A CN201710544039 A CN 201710544039A CN 107504971 A CN107504971 A CN 107504971A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
- G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/04—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by terrestrial means
- G01C21/08—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by terrestrial means involving use of the magnetic field of the earth
Abstract
The invention discloses a kind of indoor orientation method and system based on PDR and earth magnetism, localization method is based on the accelerometer, gyroscope and magnetometer being located inside smart mobile phone, obtains the geomagnetic data of localization region using magnetometer and establishes global earth magnetism reference map using Kriging regression algorithm；When user moves, the cadence, step-length and direction angle information of user is obtained using accelerometer and gyroscope, obtains PDR positioning results；The best orientation result of user is obtained finally by particle filter blending algorithm, alignment system includes measurement module, PDR locating modules, particle filter module and the display module being linked in sequence；Described measurement module further comprises accelerometer, gyroscope and magnetometer, and accelerometer, gyroscope and magnetometer are connected with PDR locating modules respectively, and magnetometer is also connected with particle filter module；By improving the precision of positioning result with reference to two kinds of location algorithms of PDR and particle filter, and the support of other external equipments is not needed to can be achieved with indoor positioning.
Description
Technical field
The present invention relates to indoor navigation technical field, specifically a kind of indoor orientation method based on PDR and earth magnetism and it is
System.
Background technology
GPS (Global Navigation Satellite System, GNSS) turned into it is military,
Many outdoor navigator fixs such as mapping, aviation, navigation, communication, electric power, traffic, meteorology, scientific research and personal navigation can not
Or scarce Main Means, but environment, the complex electromagnetic environment of malicious interference and building, ore deposit are blocked in forest, city, valley etc.
, the unavailable problems of GNSS, " last of the indoor positioning as navigator fix be present in the indoor environment such as well, tunnel, underground, underwater
Kilometer ", is always a global problem, how effectively to solve the key problem for turning into navigation and location-based service.At present
There are the research largely on indoor positioning technologies, including Wi-Fi, infrared technique IR, Bluetooth technology Blue Tooth, RFID skills
Art etc..
Existing indoor locating system generally requires to gather substantial amounts of data, Huo Zhexu to improve the matching precision of earth magnetism
External equipment is combined to realize auxiliary positioning, and these conditions all limit the application of indoor ground magnetic orientation.If for example, Wi-
Fi positioning measuring and calculating is based only upon the Wi-Fi access points currently connected, rather than the signal intensity composite diagram with reference to periphery Wi-Fi, then
Wi-Fi positioning is just easy to error be present, floor mistake is such as positioned, in addition, Wi-Fi access points generally all can only covering radius
90 meters or so of region, and be highly susceptible to the interference of other signals, so as to influence its precision, the energy consumption of locator also compared with
It is high；Because light cannot pass through barrier so that infrared-ray is only capable of line-of-sight propagation, is easily disturbed by other light, and red
The transmission range of outside line is shorter so that the poor effect of infrared technique IR indoor positionings；Bluetooth positioning is mainly used in small range
Positioning, for the space environment of complexity, the stability of bluetooth alignment system is slightly worse, is disturbed by noise signal big；RFID positions skill
Art carries out contactless bidirectional communication data exchange using RF-wise, realizes the purpose of mobile device identification and positioning, it can
To obtain the information of centimeter-level positioning precision in several milliseconds, and transmission range is big, cost is relatively low；But, because it is not easy to
It is incorporated among mobile device and the shortcomings of operating distance is short so that the scope of application of RFID location technologies is limited to.
Earth's magnetic field has similar attribute as natural physical coordinates system with gravitational field, is all the basic physics for belonging to the earth
.Longitude, latitude and it is highly different in the case of, indicated magnetic field size and Orientation is also different, in addition, magnetic field
Characteristic information is very more, there is seven variables such as magnetic field intensity, three axis components, and abundant information is provided for navigation matching.Principle
For upper, magnetic vector has unique correspondence with every bit in terrestrial space, so providing sufficient reason for earth-magnetism navigation
By foundation.Earth-magnetism navigation is most suitable in terms of information fusion is carried out with inertial navigation, and they collectively constitute integrated navigation system
System.Because earth-magnetism navigation is filtering navigation and positioning algorithm, it will not be influenceed by accumulated time error effects, and this characteristic
The accumulated error as caused by inertia device can be corrected in time.Therefore earth's magnetic field can be utilized to complete indoor positioning.This method is only
Indoor navigation work can be completed using indoor earth's magnetic field supplementary inertial device, it is not necessary to external equipment, simple to operate and application
It is convenient, accurate location navigation can be realized indoors.
The content of the invention
It is an object of the invention to overcome the deficiencies in the prior art, and provide a kind of indoor positioning based on PDR and earth magnetism
Method and system, the alignment system can complete indoor navigation merely with the sensor inside smart mobile phone and work, it is not necessary to outer
The auxiliary of portion's equipment, simple to operate and application is convenient, can realize accurate location navigation indoors.
Realizing the technical scheme of the object of the invention is：
A kind of indoor orientation method based on PDR and earth magnetism, it is based on accelerometer, the gyro being located inside smart mobile phone
Instrument and magnetometer, obtain the geomagnetic data of localization region using magnetometer and established globally using Kriging regression algorithm
Magnetic reference map；When user moves, the cadence, step-length and direction angle information of user is obtained using accelerometer and gyroscope,
So as to obtain PDR positioning results；Each data are merged finally by particle filter algorithm and obtain the best orientation result of user, are had
Body comprises the following steps：
Step S1:By the Magnetic Sensor field indoors for the smart mobile phone for being built-in with accelerometer, gyroscope and magnetometer
Ground is scanned, by the geomagnetic data collected storage into smart mobile phone, and using Kriging regression algorithm in intelligent hand
Indoor global earth magnetism reference map is established in machine；
Step S2:When user moves, by the accelerometer built in smart mobile phone and gyroscope gathered data, and by
PDR algorithms obtain the relative position of user；
Step S3:The ground magnetic value of the position correspondence is searched out in global earth magnetism reference map by relative position；
Step S4:The real-time geomagnetic data of user's walking is measured by magnetometer, and data are smoothed and tieed up
Several changes；
Step S5:The relative positioning result obtained by PDR finds corresponding ground magnetic value on partial reference figure, is filtered by particle
Itself and actual measurement geomagnetic data are carried out fusion treatment so as to obtaining the weight of each particle by ripple algorithm, calculate each particle step-length with
And the weight in direction and can obtain customer location, and the final positioning result of user is included on cell phone map.
In such scheme, the global earth magnetism reference map that is built in step S1, specific implementation process is as follows：First according to certain
Ratio draws building plan, and the point that can show construction characteristic is marked on plan, is then obtained and carried with smart mobile phone
Three axles under body coordinate ground magnetic component, completes mapping of the three axle geomagnetic datas from carrier coordinate system to world coordinate system, will gather
To data be filtered, filter out unusual point data, choose the structure that earth magnetism characteristic value completes earth magnetism reference map；Finally, pass through
Corresponding relation integrates plane structure chart and geomagnetic data, completes the structure of earth magnetism reference map.
In such scheme, in step S1 with Kriging regression method build earth magnetism reference map when, earth magnetism reference map is put down
Face is divided into the small grid of many, and with solving the central point of each grid magnetic value, when smart mobile phone gathers geomagnetic data,
5s geomagnetic data is gathered at grid vertex every 0.5m, obtains the average value of the geomagnetic data.
In such scheme, in step S2, the relative position of user must be beaten by PDR algorithms, relative position and acceleration have with
Lower relation：
In formula (1), S (ti) represent tiThe displacement of moment pedestrian, a (ti) represent tiThe deflection at moment, E (ti) and N (i)
T is represented respectivelyiThe coordinate value of moment east orientation and north orientation.
Need to know the deflection of user and the step-length of user in such scheme, in step S2, user's deflection is by quaternary
Number method obtains, and step-length has following relation with acceleration：
In formula (2), lkRepresent the step-length of user, appThe difference of acceleration peak value and valley is represented, β is scale factor, fixed
Obtained training data is obtained through least square fitting before position.
In such scheme, the magnetic vector that magnetometer measures can represent as follows：
M (r, t)=Mm(r, t)+Mc(r)+Md(r, t) (3)
In formula (3), M represents magnetic field overall strength, MmRepresent main earth's magnetic field, McRepresent earth's crust earth's magnetic field, MdRepresent interference
Earth's magnetic field, r represent carrier present position, and t represents the time.
In such scheme, in step S4 the change of dimension be by magnetic vector from three-dimensional amount be converted into two dimension amount magnetic vector, three
During dimension amount is converted into two dimension amount：M、H、The key elements of φ tetra- project M with M on three axles of terrestrial coordinate systemx,My,Mz's
Relation is as follows：
In above-mentioned formula (4), (5), (6), (7), magnetic field overall strength is represented with M, and it is projected into northeast plane obtains H,
Referred to as horizontal intensity；H is projected into East and West direction axle, obtains East and West direction field strength Mx；Similarly, north-south axle is projected onto, obtains south
North orientation field strength My；WhereinMagnetic declination is represented, φ represents magnetic dip angle.
In such scheme, the net that relative position is located at is obtained by step-size in search by known relative position in step S3
Lattice, so as to obtain corresponding geomagnetic data on local geomagnetic chart.
In such scheme, it is subjected to fusion treatment so as to obtain with earth magnetism measured data by particle filter algorithm in step S5
To final positioning result, particle filter asks the formula of particle weights as follows：
In above-mentioned formula (8), n represents observation z dimension, and we are by the use of the modulus value of magnetic field vector as observation, so n
=1, V are covariances, obs (s) represent corresponding to the current location that is obtained as geomagnetic matching magnetic value, z is with representing current location
The observation of magnetic.
A kind of indoor locating system based on PDR and earth magnetism, including measurement module, PDR locating modules, the grain being linked in sequence
Sub- filtration module and display module；Described measurement module further comprises accelerometer, gyroscope and magnetometer, acceleration
Meter, gyroscope and magnetometer are connected with PDR locating modules respectively, and magnetometer is also connected with particle filter module.
The inventive method improves the precision of positioning result by combining two kinds of location algorithms of PDR and particle filter, and
The support of other external equipments is not needed to can be achieved with indoor positioning.
Brief description of the drawings
Fig. 1 is a kind of system block diagram of indoor locating system based on PDR and earth magnetism of the present invention；
Fig. 2 is PDR location technology block schematic illustrations；
Fig. 3 is particle filter blending algorithm flow chart；
Fig. 4 is the location simulation result that PDR+ particle filters obtain；
Fig. 5 is the location simulation result that PDR+ geomagnetic matchings obtain.
Embodiment
The present invention is further elaborated with reference to the accompanying drawings and examples, but is not limitation of the invention.
Embodiment：
As shown in figure 1, a kind of indoor locating system based on PDR and earth magnetism, including measurement module, the PDR being linked in sequence
Locating module, particle filter module and display module；Described measurement module further comprises accelerometer, gyroscope and magnetic force
Meter, accelerometer, gyroscope and magnetometer are connected with PDR locating modules respectively, and magnetometer is also connected with particle filter module.
A kind of indoor orientation method based on PDR and earth magnetism, it is based on accelerometer, the gyro being located inside smart mobile phone
Instrument and magnetometer, obtain the geomagnetic data of localization region using magnetometer and established globally using Kriging regression algorithm
Magnetic reference map；When user moves, the cadence, step-length and direction angle information of user is obtained using accelerometer and gyroscope,
So as to obtain PDR positioning results；Corresponding estimation ground magnetic number is searched on global earth magnetism reference map by PDR relative position
According to, finally by particle filter algorithm merge estimation earth magnetism with actual measurement geomagnetic data obtain each particle weights, obtain each particle
Step-length and the weighted sum of deflection are that can obtain the best orientation result of user；
Wherein accelerometer is by detection quality (also referred to as sensitive-mass), supporting, potentiometer, spring, damper and housing group
Into when instrument housing accelerates with carrier along sensitive direction of principal axis, according to Newton's law, there is certain inertia
The motion state that detection quality tries hard to holding its original is constant, and it will produce relative motion between housing, make camber of spring,
Then detection quality accelerates therewith under spring force, and at this moment the deformation reflection of spring is by the size of measuring acceleration；
The traditional structure of gyroscope is that inside has individual gyro, and the operation principle of three-axis gyroscope is by perceiving three-dimensional coordinate
Angle in system between the vertical axis of gyrorotor and equipment, and angular speed is calculated, object is differentiated by angle and angular speed
In the motion state of three dimensions, three-axis gyroscope can perceive 6 directions of up, down, left, right, before and after simultaneously, can finally sentence
Break and the motion track of equipment；
Magnetometer is to measure user by regional magnetic field size and the instrument in direction, may thereby determine that the position of carrier
Put.
The number of axle of acceleration three is collected according to this and the number of axle evidence of gyroscope three by mobile phone, the acceleration information collected is passed through
Cadence detection, step-size estimation scheduling algorithm user's carrier step-length, pass through EKF and posture knot by gyro data
Calculation obtains the deflection of user, finally obtains user's relative position by PDR algorithms.
As shown in Fig. 2 it is PDR location technology block schematic illustrations.Original is measured by accelerometer, gyroscope and magnetometer
Beginning data, these initial data are obtained into the deflection of user's walking through Kalman filtering fusion treatment, utilize acceleration information
The detection of cadence and the estimation of step-length are completed, the relative position of user is finally obtained by PDR algorithms.
Particle filter refers to approximately represent that probability is close by finding one group of random sample propagated in state space
Function is spent, integral operation is replaced with sample average, and then obtains the minimum variance estimate of system mode, that is, obtains user most
Good estimated location.
As shown in figure 3, being the flow chart of particle filter algorithm, comprise the following steps：
Step S1:Existed by being built-in with the Magnetic Sensor built in the smart mobile phone of accelerometer, gyroscope and magnetometer
Covered court is scanned, and by the geomagnetic data collected storage into smart mobile phone, and is existed using Kriging regression algorithm
Indoor global earth magnetism reference map is established in smart mobile phone；
Step S2:When user moves, by the accelerometer built in smart mobile phone and gyroscope gathered data, and by
PDR algorithms obtain the relative position of user；
Step S3:By PDR relative positioning result the geomagnetic data of the position correspondence is obtained in local earth magnetism reference map；
Step S4:The real-time geomagnetic data of user's walking is measured by magnetometer, and data are smoothed and tieed up
Several changes；
Step S5:The geomagnetic data of the position correspondence is obtained in local earth magnetism reference map by PDR relative positioning result,
It is merged with real-time geomagnetic data so as to obtain the weights of particle by particle filter algorithm；
Step S6：Resampling is carried out to particle, the particle of low weight is considered as apart from user's time of day farther out, again dividing
Limited particle can be concentrated on particle in the higher region of confidence level, so we filter out according to certain probability
The particle of low weight, particle is focused in high weight particle near zone so that population finally restrains.
Step S7：By seeking the step-length of each particle and the weighted sum of deflection obtains final positioning result, and by user
Final positioning result is shown on cell phone map.
In above-mentioned technical proposal, when gathering geomagnetic data with smart mobile phone in step S1, every 0.5m collections 5s earth magnetism
Data, obtain the average value of the geomagnetic data.
In above-mentioned technical proposal, also need to build earth magnetism reference map in step S1, specific implementation process is as follows：First according to one
Fixed ratio draws building plan, and the point that can show construction characteristic is marked on plan, then obtained with smart mobile phone
With taking three axles under carrier coordinate magnetic component, mapping of the three axle geomagnetic datas from carrier coordinate system to world coordinate system is completed, will
The data collected are filtered, and filter out unusual point data, choose the structure that earth magnetism characteristic value completes earth magnetism reference map；Finally,
Plane structure chart and geomagnetic data are integrated by corresponding relation, complete the structure of earth magnetism reference map.
In above-mentioned technical proposal, by earth magnetism base when the earth magnetism reference map built with Kriging regression method in step S1
Quasi- plan is divided into the small grid of many, and with solving the central point of each grid magnetic value.
In above-mentioned technical proposal, need that the relative position of user must be beaten by PDR algorithms in step S2, relative position is with accelerating
Degree has following relation：
In above-mentioned formula (1), S (ti) represent tiThe displacement of moment pedestrian, a (ti) represent tiThe deflection at moment, E (ti) and
N (i) represents t respectivelyiThe coordinate value of moment east orientation and north orientation.
Need to know the step-length of user in above-mentioned technical proposal, in step S2, step-length has following relation with acceleration：
In above-mentioned formula (2), lkRepresent the step-length of user, appRepresent the difference of acceleration peak value and valley, β be ratio because
Son, obtained training data is obtained through least square fitting before positioning.
Need to know the deflection of user in above-mentioned technical proposal, in step S2, user's deflection is obtained by Quaternion Method.
The estimation of deflection is typically realized by the combination of magnetometer, accelerometer, more multiple yet with the electromagnetic environment of interior
Miscellaneous, the angle measured according to electronic compass, which has very big fluctuation, to be occurred, and such case just needs to introduce EKF
Fusion correction is carried out, gyroscope can measure angular velocity of rotation, can obtain the changing value of angle so as to carry out integration, at present
Middle-end smart mobile phone all supports gyroscope substantially, is obtained relatively so electronic compass and gyroscope are carried out into data fusion
Stable direction estimation.
In above-mentioned steps S3, the magnetic vector that magnetometer measures can represent as follows：
M (r, t)=Mm(r, t)+Mc(r)+Md(r, t) (3)
Wherein, M represents magnetic field overall strength, MmRepresent main earth's magnetic field, McRepresent earth's crust earth's magnetic field, MdInterference earth's magnetic field is represented,
R represents carrier present position, and t represents the time.
In above-mentioned steps S4, the change of dimension is that magnetic vector is converted into two dimension amount magnetic vector from three-dimensional amount, and three-dimensional amount turns
During turning to two dimension amount：M、H、The key elements of φ tetra- project M with M on three axles of terrestrial coordinate systemx,My,MzRelation such as
Under：
In above-mentioned formula (4), (5), (6), (7), magnetic field overall strength is represented with M, and it is projected into northeast plane obtains H,
Referred to as horizontal intensity；H is projected into East and West direction axle, obtains East and West direction field strength Mx；Similarly, north-south axle is projected onto, obtains south
North orientation field strength My；WhereinMagnetic declination is represented, φ represents magnetic dip angle.
In above-mentioned technical proposal, the grid that relative position is located at is obtained by known relative position in step S5, globally
Geomagnetic data corresponding to the grid is found on magnetic reference map, grid geomagnetic data and real-time geomagnetic data are passed through into particle filter
Algorithm fusion obtains each particle weights, asks particle weighted sum to obtain customer location, and particle filter algorithm merges geomagnetic data
Formula is as follows when seeking particle weights：
In above-mentioned formula (8), n represents observation z dimension, and we are by the use of the modulus value of magnetic field vector as observation, so n
=1, V are covariances, obs (s) represent corresponding to the current location that is obtained as geomagnetic matching magnetic value, z is with representing current location
The observation of magnetic.
As shown in Figure 4, Figure 5, the simulation result respectively obtained by PDR+ particle filters and PDR+ geomagnetic matchings, by Fig. 4
It can be seen that the positioning result of particle filter can't especially rely on PDR result, when PDR deviation actual paths are more and more remote
When, correction positioning result that particle filter can be adaptive so that position error is not too large, finally it can be seen that positioning rail
Mark is basically identical with reference locus；By Fig. 5, it can be seen that, geomagnetic matching algorithm especially relies on PDR positioning result, when PDR is inclined
When difference causes greatly very much positioning result beyond the scope of global earth magnetism reference map, geomagnetic matching algorithm is searched in specified search radius
For rope less than suitable geomagnetic matching point, it can only trust PDR positioning result completely, finally result in positioning failure, geomagnetic matching
The positioning track of algorithm completely offsets from reference locus.
The simulation result of comparison diagram 4 and Fig. 5, the performance that can obtain particle filter algorithm are better than geomagnetic matching algorithm,
It can break away from the dependence to PDR algorithms, and in position fixing process, it is according to the dynamic adjusting step of weight size of particle
And the size of deflection, it can finally obtain more accurate positioning result.
Claims (10)
1. a kind of indoor orientation method based on PDR and earth magnetism, it is characterised in that be based on the acceleration being located inside smart mobile phone
Degree meter, gyroscope and magnetometer, are obtained the geomagnetic data of localization region using magnetometer and are built using Kriging regression algorithm
Found global earth magnetism reference map；When user moves, the cadence, step-length and direction of user is obtained using accelerometer and gyroscope
Angle information, so as to obtain PDR positioning results, so as to obtain the geomagnetic data of the position correspondence on global earth magnetism reference map；Most
The best orientation result of user is obtained by particle filter algorithm afterwards, specifically comprised the following steps：
Step S1:By being built-in with the Magnetic Sensor of smart mobile phone of accelerometer, gyroscope and magnetometer, place is entered indoors
Row scanning, by the geomagnetic data collected storage into smart mobile phone, and using Kriging regression algorithm in smart mobile phone
Establish indoor global earth magnetism reference map；
Step S2:When user moves, calculated by the accelerometer built in smart mobile phone and gyroscope gathered data, and by PDR
Method obtains the relative position of user；
Step S3:By PDR relative positioning result the geomagnetic data of the position correspondence is obtained in local earth magnetism reference map；
Step S4:The real-time geomagnetic data of user's walking is measured by magnetometer, and data are smoothed and dimension
Change；
Step S5:The geomagnetic data of the position correspondence is obtained in local earth magnetism reference map by PDR relative positioning result, is passed through
Particle filter algorithm merges it so as to obtain the weights of particle with real-time geomagnetic data；
Step S6：Resampling is carried out to particle, the particle of low weight is considered as apart from user's time of day farther out, redistributing grain
Son can concentrate on limited particle in the higher region of confidence level, so we filter out low weight according to certain probability
Particle, particle is focused in high weight particle near zone so that population finally restrains.
Step S7：By asking the step-length of each particle and the weighted sum of deflection to obtain final positioning result, and user is final
Positioning result is shown on cell phone map.
2. localization method according to claim 1, it is characterised in that the global earth magnetism reference map built in step S1, tool
Body implementation process is as follows：Building plan first is drawn according to certain ratio, the point mark of construction characteristic will can be shown flat
On the figure of face, the three axles ground magnetic component under carrier coordinate is then obtained with smart mobile phone, completes three axle geomagnetic datas from carrier coordinate
It is the mapping to world coordinate system, the data collected is filtered, filter out unusual point data, chooses earth magnetism characteristic value and complete
The structure of earth magnetism reference map；Finally, plane structure chart and geomagnetic data are integrated by corresponding relation, completes the structure of earth magnetism reference map
Build.
3. localization method according to claim 1, it is characterised in that the earth magnetism built in step S1 with Kriging regression method
Reference map when, earth magnetism benchmark plan is divided into the small grid of many, and with solving the central point of each grid magnetic value,
When smart mobile phone gathers geomagnetic data, 5s geomagnetic data is gathered at grid vertex every 0.5m, obtains the geomagnetic data
Average value.
4. localization method according to claim 1, it is characterised in that in step S2, the relative of user must be beaten by PDR algorithms
Position, relative position have following relation with acceleration：
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Wherein, s (ti) represent tiThe displacement of moment pedestrian, a (ti) represent tiThe deflection at moment, E (ti) and N (i) represent respectively
tiThe coordinate value of moment east orientation and north orientation.
5. localization method according to claim 1, it is characterised in that need to know the deflection of user and use in step S2
The step-length at family, user's deflection are obtained by Quaternion Method, and step-length has following relation with acceleration：
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lkRepresent the step-length of user, appRepresent the difference of acceleration peak value and valley, β is scale factor, will be obtained before positioning
Training data obtains through least square fitting.
6. localization method according to claim 1, it is characterised in that the magnetic vector that magnetometer measures can represent such as
Under：
M (r, t)=Mm(r, t)+Mc(r)+Md(r, t)
Wherein, M represents magnetic field overall strength, MmRepresent main earth's magnetic field, McRepresent earth's crust earth's magnetic field, MdRepresent interference earth's magnetic field, r tables
Show carrier present position, t represents the time.
7. localization method according to claim 1, it is characterised in that the change of dimension is from three by magnetic vector in step S4
Dimension amount is converted into two dimension amount magnetic vector, during three-dimensional amount is converted into two dimension amount：M、H、The key elements of φ tetra- are sat with M in the earth
M is projected on three axles of mark systemx,My,MzRelation it is as follows：
<mrow>
<mi>M</mi>
<mo>=</mo>
<msqrt>
<mrow>
<msup>
<msub>
<mi>M</mi>
<mi>x</mi>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>M</mi>
<mi>y</mi>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>M</mi>
<mi>z</mi>
</msub>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
</mrow>
<mrow>
<mi>H</mi>
<mo>=</mo>
<msqrt>
<mrow>
<msup>
<msub>
<mi>M</mi>
<mi>x</mi>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<msup>
<msub>
<mi>M</mi>
<mi>y</mi>
</msub>
<mn>2</mn>
</msup>
</mrow>
</msqrt>
</mrow>
In formula, magnetic field overall strength is represented with M, and it is projected into northeast plane obtains H, referred to as horizontal intensity；H is projected into thing
To axle, East and West direction field strength M is obtainedx；Similarly, north-south axle is projected onto, obtains north-south field strength My；WhereinRepresent magnetic declination,
φ represents magnetic dip angle.
8. localization method according to claim 1, it is characterised in that by PDR relative positioning result complete in step S3
The geomagnetic data of the position correspondence is obtained in local magnetic reference map, grid geomagnetic data and real-time geomagnetic data are filtered by particle
Ripple algorithm fusion obtains each particle weights, asks weighted sum to obtain customer location the step-length and deflection of particle.
9. localization method according to claim 1, it is characterised in that by particle filter algorithm by geomagnetic data in step S5
Formula is as follows when particle weights are sought in fusion：
<mfenced open = "" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<msubsup>
<mi>&omega;</mi>
<mi>i</mi>
<mrow>
<mi>k</mi>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msubsup>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<mrow>
<msup>
<mrow>
<mo>(</mo>
<mn>2</mn>
<mi>&pi;</mi>
<mo>)</mo>
</mrow>
<mfrac>
<mi>n</mi>
<mn>2</mn>
</mfrac>
</msup>
<msup>
<mrow>
<mo>|</mo>
<mi>V</mi>
<mo>|</mo>
</mrow>
<mfrac>
<mn>1</mn>
<mn>2</mn>
</mfrac>
</msup>
</mrow>
</mfrac>
<mi>exp</mi>
<mo>{</mo>
<mo>-</mo>
<mfrac>
<mn>1</mn>
<mn>2</mn>
</mfrac>
<msup>
<mrow>
<mo>&lsqb;</mo>
<mrow>
<mo>(</mo>
<msup>
<mi>z</mi>
<mrow>
<mi>k</mi>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msup>
<mo>-</mo>
<msup>
<mi>z</mi>
<mi>k</mi>
</msup>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mi>o</mi>
<mi>b</mi>
<mi>s</mi>
<mo>(</mo>
<msubsup>
<mi>s</mi>
<mi>i</mi>
<mrow>
<mi>k</mi>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msubsup>
<mo>)</mo>
<mo>-</mo>
<mi>o</mi>
<mi>b</mi>
<mi>s</mi>
<mo>(</mo>
<msubsup>
<mi>s</mi>
<mi>i</mi>
<mi>k</mi>
</msubsup>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>&rsqb;</mo>
</mrow>
<mi>T</mi>
</msup>
<msup>
<mi>V</mi>
<mrow>
<mo>-</mo>
<mn>1</mn>
</mrow>
</msup>
<mo>&lsqb;</mo>
<mrow>
<mo>(</mo>
<msup>
<mi>z</mi>
<mrow>
<mi>k</mi>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msup>
<mo>-</mo>
<msup>
<mi>z</mi>
<mi>k</mi>
</msup>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mi>o</mi>
<mi>b</mi>
<mi>s</mi>
<mo>(</mo>
<msubsup>
<mi>s</mi>
<mi>i</mi>
<mrow>
<mi>k</mi>
<mo>+</mo>
<mn>1</mn>
</mrow>
</msubsup>
<mo>)</mo>
<mo>-</mo>
<mi>o</mi>
<mi>b</mi>
<mi>s</mi>
<mo>(</mo>
<msubsup>
<mi>s</mi>
<mi>i</mi>
<mi>k</mi>
</msubsup>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>&rsqb;</mo>
<mo>}</mo>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
Wherein, n represents observation z dimension, and we are by the use of the modulus value of magnetic field vector as observation, so n=1, V are association sides
Difference, corresponding to the current location that obs (s) represents to be obtained as geomagnetic matching magnetic value, z represent the observation of current location earth magnetism.
10. a kind of indoor locating system based on PDR and earth magnetism, it is characterised in that including measurement module, the PDR being linked in sequence
Locating module, particle filter module and display module；Described measurement module further comprises accelerometer, gyroscope and magnetic force
Meter, accelerometer, gyroscope and magnetometer are connected with PDR locating modules respectively, and magnetometer is also connected with particle filter module.
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